Quarto: a very short introduction

What is Quarto?

• Quarto is an open-source scientific and technical publishing system;
• can be used to create reports, dashboards, presentations, websites;
• possible to mix text and executable code (R, Python);
• output is dynamic and reproducible;
• useful for repetitive and data-driven reporting.

Logo from https://quarto-dev.github.io/quarto-r/

Example: admissions reports

• During each admissions cycle, tutors look at the application cohort, e.g.

  • number and sociodemographic profile of applicants;

  • distribution of admissions measures by characteristics of interest (gender, deprivation status, schooling);

  • comparisons with previous years and/or across the university.

• Ca. 40 descriptive statistics reports are produced each year:

  • very similar in structure… but not the same!

Example report: one admissions metric

Example report: two admissions metrics

Example report: comparison across admissions years

Copy-pasting approach

Can the workflow be made more efficient?

What parts of the workflow can be automated?

Example automation

Example automation

Example automation

How can Quarto help?

• Report is parameterised (e.g. input database, UCAS cycle, document style, repetitive footnote string, characteristic of interest);

• one-click update at database change (e.g. bug fixes);

• one analysis, multiple formats (e.g. pdf output; links colour; missing data display);

• possible to include executable analysis code, so all numbers are reproducible;

• cross-referencing, interactive graphs, integration with R, Python, LaTeX…

How to get started

• Install software: Quarto; text editor (Posit/RStudio, Positron, VS Code); R, Python.
• Create a script:
  • typically a .qmd file;
  • YAML (document settings);
  • main body (text, figures, tables);
  • further documents (e.g. .css files).
• Render (or preview).
• Output formats:
  • .html: interactive and good for complex structure;
  • .pdf: print-ready;
  • .docx: for collaboration.

YAML (YAML Ain’t Markup Language)

• Human-friendly way to specify document settings;
• front matter at the top of the file;
• use three dashes --- to start and end the YAML block.

---
title: "My first Quarto report"
author: "Jane Doe"
format: html
---

YAML for this presentation

---
title: "Quarto: a very short introduction"
author: "Iryna Schlackow; SDI/EPS"
date: "06 August 2025"
format: 
  revealjs:                    # output is .html slides
    smaller: true              # scale down default fonts
    css: styles.css            # further adjustments of the default style
    slide-number: "c/t"        # slide numbering
    embed-resources: true      # embed all figures so that .html can be shared
    code-copy: true            # add button for copying code
    code-block-bg: "#d0dff2"   # style of coding blocks
    code-block-border-left: "#002147"
    highlight-style: github
execute:                      # code execution options to prevent unwanted messages
  echo: false
  warning: false
  message: false
fig-cap-location: top         # figure captions above
tbl-cap-location: top         # table captions above
---

Main body

• Markdown syntax (there is a cheat sheet);

• generally plain text format but there are WYSIWYM options (e.g. RStudio Visual Editor).

Lists and fonts

* You
* can
* create
  - nested
* lists

1. also text in **bold** and *italic*, and
1. numbered items

• You
• can
• create
  • nested
• lists

1. also text in bold and italic, and

2. numbered items

Tables

data <- data.frame(
  name = c("Alice", "Bob", "Charlie"),
  score = c(90, 85, 88),
  score2 = c(54, 20, 60))
  
kable(data, caption = "PAT scores")

Tables

data <- data.frame(
  name = c("Alice", "Bob", "Charlie"),
  score = c(90, 85, 88))
  
kable(data, caption = "PAT scores") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "responsive", "condensed")) %>%
  row_spec(0, bold = TRUE, color = "white", background = "#002147") %>%
  add_header_above(c(" " = 1, "PAT score" = 2)) %>%
  pack_rows("Female students", 1, 1) %>% 
  pack_rows("Male students", 2, 3)

Cross-referencing

# We can do numbered sections {#sec-numbered}

## With numbered subsection {#sec-numbered-subsection}

![Rewley House on Wellington Square.](https://upload.wikimedia.org/wikipedia/commons/a/a1/Rewley_House_-_geograph.org.uk_-_1126209.jpg){#fig-rewley}

See @fig-rewley from @sec-numbered-subsection for the buildings near the University Offices.

# AND we can do unnumbered sections! {.unnumbered}

Tabsets

::: {.panel-tabset}

##### First tab

This is in the first tab.

##### Second tab

This is in the second tab. We can also add graphs and tables here. And even write inline $\exp^{\textrm{i}\pi} = -1$ and displaymath $\LaTeX$ equations $$\sum_{i=1}^\infty \frac{1}{i^2} = \frac{\pi^2}{6}.$$

:::

Which looks like this:

Example HTML output

Engineering gender gap report

Example dashboard

Penguin dashboard; courtesy of Craig Smith & Connair Russell-Wilks (UAO).

How much coding is required?

• It depends! Not much for basic reporting.
• There are cheat sheets for everything.
• Embedded analyses require R (or Python).
• Fine-tuning display options might need CSS.
• AI can help (code snippets; within-editor integration).

The concept of gRammar

• Many R packages use grammar to build complex outputs from simple components.
• A consistent set of verbs is used to perform data manipulation.
• Output is constructed step-by-step by putting these verbs into layers.
• Layers are connected by %>% or +.

Summary: the benefits of Quarto

• Output reproducibility;
• automation of repetitive reports;
• structured and consistent formatting with themes and templates;
• software integration (R, Python, CSS);
• lots of random cool features;
• version control;
• learning curve but lots of documentation, cheat sheets and AI help.

Image from https://drpicox.medium.com/do-not-automate-is-costlier-that-it-seems-118dce13a55c